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Automatic encoding into SNOMED III: a preliminary investigation

N Sager1, M Lyman, N T Nhàn

  • 1Courant Institute of Mathematical Sciences, New York University, NY 10012.

Proceedings. Symposium on Computer Applications in Medical Care
|January 1, 1994
PubMed
Summary
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This study developed a method to convert clinical reports into structured patient data using the Linguistic String Project (LSP) medical language processing (MLP) system. The system

Area of Science:

  • Medical Informatics
  • Natural Language Processing

Background:

  • Clinical narrative reports contain valuable patient data.
  • Manual data extraction from clinical reports is time-consuming and prone to errors.

Purpose of the Study:

  • To develop a procedure for mapping the output of the Linguistic String Project (LSP) medical language processing (MLP) system into SNOMED III codes.
  • To enable automated conversion of narrative clinical data into structured, coded formats.

Main Methods:

  • Utilized the Linguistic String Project (LSP) medical language processing (MLP) system to parse narrative clinical reports.
  • Developed a mapping procedure to translate LSP MLP output into SNOMED III terminology.
  • Evaluated preliminary results of the mapping process.

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Main Results:

  • Successfully developed a procedure for mapping LSP MLP output to SNOMED III codes.
  • Demonstrated the feasibility of converting unstructured clinical text into structured, coded patient data.
  • Identified preliminary results and requirements for further system development.

Conclusions:

  • The developed procedure facilitates the transformation of narrative clinical data into SNOMED III codes.
  • Automated coding of clinical reports enhances data accessibility and usability for research and clinical practice.
  • Further development is required to optimize the mapping process and expand its applicability.